Risk factors for fractures and avascular osteonecrosis in type 1 Gaucher disease: A study from the International Collaborative Gaucher Group (ICGG) Gaucher Registry
Bibliographic record
Abstract
We hypothesized that overall disease activity or the severity of involvement of individual disease compartments, as measured by clinical and surrogate markers, predict the risk of avascular osteonecrosis (AVN) or fractures in type 1 Gaucher disease (GD1). We applied our risk-set matched case-control method to identify four patient groups within the International Collaborative Gaucher Group (ICGG) Gaucher Registry based on the presence and absence of AVN and fractures. Characteristics of GD1 were examined by comparing the distributions of each risk factor in cases versus matched controls using conditional logistic regression to calculate adjusted odds ratios (OR). Potential risk factors included hematological and visceral parameters, GD1 biomarkers, white blood cells, GBA1 genotype, and spine and femur dual-energy X-ray absorptiometry (DXA) Z-scores. In the total population of 5894 ICGG Gaucher Registry patients, 544 experienced at least one episode of AVN; 2008 reported no history of AVN. Clinical and surrogate markers of disease activity were similar in patients with and without AVN; patients with AVN were 1.6 times more likely to be anemic compared to matched controls (OR = 1.59; 95% confidence interval [CI], 1.06-2.38, p < 0.05). For fractures, 319 patients suffered fractures and 1233 had no prior history of fractures. Clinical and surrogate markers of disease in patients with and without fractures were similar, except for mean lumbar spine DXA Z-scores. Among patients with fractures, 49.3% had DXA Z-scores ≤ -1 compared to 31.0% in the control group. Compared to controls with Z-scores > -1.0, GD1 patients exhibiting Z-scores ≤ -1 had an OR of 5.55 (95% CI, 1.81-17.02, p < 0.01) for fracture. In GD1, after controlling for gender, year of birth, treatment status, and splenectomy status, we identified new risk factors for AVN and fractures. Concurrent anemia was associated with an increased risk for AVN. Low bone mineral density of the lumbar spine was a strong risk factor for fractures of the spine and femur in GD1.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".